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Agent Einstein — Crypto & Market Intelligence

Arbitrage Scanner

find_arbitrage
Read-onlyIdempotent

Scan for live arbitrage: DEX price dislocations, flash-loan-fundable routes, cross-chain spreads, or prediction-market mispricings. [Paid: $0.60–$1.00 per call from your Einstein credit balance. Free alternatives exist for several of these — see list_einstein_capabilities.]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNodex · flashloan · cross_chain · prediction_market.dex
chainNoBlockchain network.base
limitNoMaximum results (1-100).

TDQS

A4.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, making the safety profile clear. The description adds valuable cost information ($0.60–$1.00 per call) and highlights that free alternatives exist, which the annotations do not convey. This extra context about cost and alternatives is useful beyond the structure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single focused sentence followed by a brief cost note. It front-loads the core purpose and then presents important cost information without any fluff. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple with 3 optional parameters and no output schema, so explaining return values is not critical. The description covers the main scope and cost. A minor gap is not mentioning the output format, but the name and description strongly imply a list of arbitrage opportunities.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds semantic richness by mapping the enum values to real-world arbitrage categories (DEX price dislocations, flash-loan-fundable routes, cross-chain spreads, prediction-market mispricings), which enhances understanding of the 'kind' parameter beyond the schema's terse enumeration. It does not add syntax details but provides meaningful context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool scans for live arbitrage and enumerates four specific categories (DEX, flash-loan, cross-chain, prediction-market). This distinct resource and scope differentiate it from siblings like scan_market or find_yield. The verb 'scan' plus the explicit resource 'live arbitrage' is specific and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly notes the tool is paid and directs users to list_einstein_capabilities for free alternatives, providing practical cost-based guidance. It implies usage for arbitrage scanning but does not contrast with specific sibling tools like detect_mev or find_yield, so it falls just short of the highest tier.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.3/5.0
Disambiguation2/5

With 40 tools, many share overlapping domains: get_smart_money_flow vs get_smart_money_inflow, scan_launchpads vs get_launchpad_radar, track_whales vs get_hyperliquid_whales, and check_token_safety vs analyze_token_security. The detailed descriptions help, but the boundaries are not always clear, making misselection likely.

Naming Consistency2/5

The tool names employ a wide variety of verbs (get_, analyze_, scan_, track_, find_, generate_, recommend_, run_, list_, ask_, assess_, detect_) with no consistent pattern. While all use snake_case, the inconsistent verb choices and occasional deviations like forecast_chart prevent predictability.

Tool Count2/5

40 tools is well above the typical 3-15 well-scoped range and exceeds the 25+ threshold for 'too many'. While the broad 'crypto intelligence' purpose justifies some breadth, the sheer number makes the surface unwieldy and suggests a lack of focused scoping.

Completeness4/5

The tool set covers a wide range of crypto intelligence domains: market analysis, forecasting, whale tracking, yield/arbitrage, security checks, prediction markets, backtesting, and even content generation. Missing operations are minor (e.g., no direct portfolio management), but core analysis and data retrieval workflows are well represented.